This is part three of our series designed to help leaders manage the various challenges they’re encountering due to COVID-19. Kepler’s advanced Machine Learning (ML) and Deep Learning capabilities can empower manufacturing organizations to discover key cost-saving insights, quickly. In the AI for manufacturing space, Kepler’s Automated Data Science Workflows are usable by anyone with data and a use case to tackle, ensuring organizations have the ability to weather today’s storm, tomorrow’s challenge, and the foggy future.
In the midst of the rapid lifestyle changes incurred by COVID-19, consumer behaviors have shifted considerably: grocery and variety stores are experiencing consistent spikes in consumer demand, while other brick-and-mortar retailers are experiencing dwindling sales and a spike in traffic to their ecommerce sites.
Undoubtedly, this reality significantly impacts manufacturers who, by and large, are worried about what COVID-19 will mean for their organizations in the short to medium terms. In fact, PwC has reported that 80% of manufacturing leaders expect to see a negative financial impact on their business due to the pandemic.
While the production, distribution and delivery of essential goods has increased exponentially, manufacturers specializing in nonessential goods are navigating murky waters where various factors are affecting demands for their products. Plus, some may be retooling their lines entirely to provide critical goods to front-line workers, including face masks, hand sanitizers, ventilators, and much more.
The complexities embedded within this sector across the globe are highlighted in a recent Gartner report, which illustrates the extent to which supply chain disruptions will reverberate across multiple industries, all of which will be experiencing the following roadblocks:
On the other hand, the heightened need for goods deemed essential are placing undue pressure on production lines, all while leaders are trying to keep their workers safe and healthy in close quarters. And those who are experiencing intense demand pressures right now may encounter a different type of pressure soon: A McKinsey survey reveals that 59% of respondents intend to exercise more caution in their spending than usual due to changes in the economy and their personal finances.
While many companies across the globe have transitioned to working remotely, for the manufacturing sector, which employs 13M Americans, that isn’t an option. There are number of course-altering decisions confronting leaders today, that range from choosing to slow down, pause, change production lines, to find more efficient means of delivering on mounting customer demands, and ensuring teams remain healthy and safe.
The good news? There are ways that Machine Learning can help solve critical challenges that will serve you now. And, while it’s tough to see the light at the end of the tunnel right now, organizations who use this opportunity to find efficiencies today could see positive results that will carry them through the pandemic and beyond.
Kepler’s Automated Data Science Workflows can help you make the right decisions, day after day, with Machine Learning that’s usable by anyone on your team.
Data Type: Tabular
Planning strategically with the most current, available information has never been more important. Kepler can help you solve essential use cases to tackle production and distribution optimization, including demand forecasting and strategic workforce planning.
As demands for products shift, ensuring your staffing needs are met to run smooth production lines is crucial. Strategic workforce planning allows you to assess labor shortages across various departments in your business, encompassing the following processes:
Kepler’s Automated Data Science Workflow for Time Series Forecasting can significantly simplify these various staffing lifecycle stages, and make workforce planning strategy a more efficient process that’s backed by richer insights. With Time Series Forecasting, you can streamline and simplify the management of various units within your organization, all with the goal of anticipating present and upcoming workforce planning needs.
Time Series Forecasting also has the power to help you plan effectively for demand by gleaning key insights to augment your planning abilities based off of key shifts in the market and consumer demands. With this workflow, you can better forecast demand by leveraging multiple tabular data sources to get a comprehensive picture of the end-to-end supply chain: leverage historical sales and performance data to prepare for upcoming seasons — or possible dips in the economy — to adjust your pricing, limit costs, and ultimately boost your bottom line.
Overall, Kepler’s Automated Data Science Workflow for Time Series Forecasting allows manufacturers to better prepare for the days, weeks, and months ahead. Whether that’s through understanding what regions may need certain products at scale, or by ensuring you have enough manpower to get key jobs done, having the right information available from the richest data is a critical success factor that all leaders should be focusing on in order to make the best possible decision at every turn.